variational inference

Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference NeurIPS 2017 Stochastic Recurrent Neural Network for Speech Recognition Interspeech 2017 Structured Bayesian Pruning via Log-Normal Multiplicative Noise NeurIPS 2017 Tensor Decomposition with Missing Indices IJCAI 2017 Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis AISTATS 2017 Tied Variational Autoencoder Backends for i-Vector Speaker Recognition Interspeech 2017 Tomography of the London Underground: a Scalable Model for Origin-Destination Data NeurIPS 2017 Variational Bayesian Multiple Instance Learning With Gaussian Processes CVPR 2017 Variational Boosting: Iteratively Refining Posterior Approximations ICML 2017 Variational Inference for Gaussian Process Models with Linear Complexity NeurIPS 2017 Variational Inference for Sparse and Undirected Models ICML 2017 Variational Inference via χ Upper Bound Minimization NeurIPS 2017 Variational Memory Addressing in Generative Models NeurIPS 2017 Variational Mixtures of Gaussian Processes for Classification IJCAI 2017 Variational Particle Approximations JMLR 2017 Variational Policy for Guiding Point Processes ICML 2017 Variational Recurrent Neural Networks for Speech Separation Interspeech 2017 Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net NeurIPS 2017 VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning NeurIPS 2017 Z-Forcing: Training Stochastic Recurrent Networks NeurIPS 2017 A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016 A Field Model for Repairing 3D Shapes CVPR 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation ICML 2016 An Architecture for Deep, Hierarchical Generative Models NeurIPS 2016